#862721 (PyPy3) No.5007 Steiner Space Travel

提出ソース

結果

問題	No.5007 Steiner Space Travel
ユーザー	dna4_
提出日時	2023-04-25 01:46:19
言語	PyPy3 (7.3.15)
結果	AC
実行時間	969 ms / 1,000 ms
コード長	10,674 bytes
コンパイル時間	634 ms
コンパイル使用メモリ	87,292 KB
実行使用メモリ	97,856 KB
スコア	8,262,348
最終ジャッジ日時	2023-04-25 01:47:02
合計ジャッジ時間	32,394 ms
ジャッジサーバーID （参考情報）	judge13 / judge12
	純コード判定しない問題か言語

このコードへのチャレンジ
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テストケース

テストケース表示

入力	結果	実行時間実行使用メモリ
testcase_00	AC	927 ms 94,616 KB
testcase_01	AC	949 ms 96,148 KB
testcase_02	AC	930 ms 96,188 KB
testcase_03	AC	935 ms 94,588 KB
testcase_04	AC	949 ms 92,144 KB
testcase_05	AC	954 ms 95,292 KB
testcase_06	AC	946 ms 95,960 KB
testcase_07	AC	922 ms 96,924 KB
testcase_08	AC	950 ms 96,436 KB
testcase_09	AC	946 ms 97,288 KB
testcase_10	AC	939 ms 97,856 KB
testcase_11	AC	918 ms 95,800 KB
testcase_12	AC	945 ms 96,648 KB
testcase_13	AC	926 ms 95,420 KB
testcase_14	AC	929 ms 95,972 KB
testcase_15	AC	937 ms 95,284 KB
testcase_16	AC	925 ms 94,044 KB
testcase_17	AC	967 ms 94,948 KB
testcase_18	AC	961 ms 94,516 KB
testcase_19	AC	921 ms 96,472 KB
testcase_20	AC	969 ms 96,344 KB
testcase_21	AC	933 ms 97,736 KB
testcase_22	AC	951 ms 95,444 KB
testcase_23	AC	968 ms 96,584 KB
testcase_24	AC	928 ms 95,432 KB
testcase_25	AC	925 ms 94,964 KB
testcase_26	AC	938 ms 96,724 KB
testcase_27	AC	926 ms 96,528 KB
testcase_28	AC	943 ms 94,352 KB
testcase_29	AC	969 ms 96,224 KB

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ソースコード

raw source code

import sys
import time
import random
import math
import heapq
from collections import defaultdict

random.seed(42)

INF = 10**18

alpha = 5
alpha2 = alpha * alpha

def eprint(*args, **kwargs):
    print(*args, file=sys.stderr, **kwargs)

class TimeKeeper:
    """
    時間を管理するクラス
    時間制限を秒単位で指定してインスタンスをつくる
    """
 
    def __init__(self, time_threshold) -> None:
        self.start_time_ = time.time()
        self.time_threshold_ = time_threshold
 
    def isTimeOver(self) -> bool:
        """
        インスタンスを生成した時から指定した時間制限を超過したか判断する  
        超過している場合にTrue  
        """
        return time.time() - self.start_time_ - self.time_threshold_ >= 0
 
    def time_msec(self) -> int:
        """経過時間をミリ秒単位で返す"""
        return int((time.time() - self.start_time_) * 1000)

    def time_sec(self) -> int:
        """経過時間を秒単位で返す(time_msecの使用を推奨)"""
        return time.time()-self.start_time_

class Kmeans:
    
    def __init__(self, X:list, n_data:int, k:int):
        self.x = [[t.x, t.y] for t in X]
        self.n_data = n_data
        self.k = k

    def init_centroid(self):
        idx = random.sample(range(self.n_data), self.k)
        centroids = [self.x[i] for i in idx]
        return centroids
    
    def compute_distance(self, centroids):
        distances = []
        for x in self.x:
            dist = [math.sqrt(sum([(a - b) ** 2 for a, b in zip(x, centroid)])) for centroid in centroids]
            distances.append(dist)
        return distances
    
    def clustering(self):
        centroids = self.init_centroid()
        new_cluster = [0]*self.n_data
        cluster = [0]*self.n_data
        for epoch in range(300):
            distances = self.compute_distance(centroids)
            new_cluster = [min(range(len(d)), key=lambda i: d[i]) for d in distances]
            for idx_centroid in range(self.k):
                x_in_cluster = [self.x[i] for i in range(self.n_data) if new_cluster[i] == idx_centroid]
                if x_in_cluster:
                    centroids[idx_centroid] = [int(sum(coord)/len(x_in_cluster)) for coord in zip(*x_in_cluster)]
            if new_cluster == cluster:
                break
        cluster = new_cluster
        return centroids


class Input:
    def __init__(self, N:int, M:int, ab:list) -> None:
        self.N = N
        self.M = M
        self.ab = ab

class Parser:

    def __init__(self, input_type:int):
        self.flag = input_type

    def parse(self):
        if self.flag == -1:
            inp:Input = self.parse_input()
        else:
            inp:Input = self.parse_input_file(self.flag)
        return inp
    
    def parse_input(self) -> Input:
        N,M = map(int,input().split())
        ab = [list(map(int,input().split())) for i in range(N)]
        return Input(N,M,ab)


    def parse_input_file(self,num) -> Input:
        cnt = str(num).zfill(4)
        PATH = f"./in/{cnt}.txt"
        with open(PATH) as f:
            l = [s.strip() for s in f.readlines()]
            N, M = map(int,l[0].split())
            ab = [list(map(int,s.split())) for s in l[1:]]
            return Input(N, M, ab)

class Transit:

    def __init__(self, id:int, x:int, y:int, type:int) -> None:
        """
        id:int id of planet or station
        x:int x coordinate
        y:int y coordinate
        type:int 1 planet, 2 station
        """
        self.id = id
        self.x = x
        self.y = y
        self.type = type
        self.key = self.type * 1000 + self.id

    def __lt__(self, other) -> bool:
        return self.key < other.key
    
    def __eq__(self, other) -> bool:
        return self.key == other.key
    
    def __str__(self) -> str:
        return f"({self.id},{self.x},{self.y},{self.type})"

class State:
    
    def __init__(self, order:list, planets:list, stations:list) -> None:
        """
        order:list visited order 
        stations:list[(int,int)] coordinates of space station
        """
        self.order = order
        self.planets = planets
        self.stations = stations
        self.links = self.prepare_edges()
        #eprint(self.links)
    
    def prepare_edges(self):
        """
        edges:dictを返す
        edges[Transit_from_key:int] = [(dist, Transit_to), ...]
        """
        edges = defaultdict(list)
        for planet_from in self.planets:
            for planet_to in self.planets: # planet to planet
                if planet_from == planet_to: continue
                edges[planet_from.key].append((self.cal_dist(planet_from, planet_to), planet_to))
            for station_to in self.stations: # planet to station
                edges[planet_from.key].append((self.cal_dist(planet_from, station_to), station_to))
        for station_from in self.stations: # station to station
            for planet_to in self.planets:
                edges[station_from.key].append((self.cal_dist(station_from, planet_to), planet_to))
            for station_to in self.stations:
                if station_from == station_to: continue
                edges[station_from.key].append((self.cal_dist(station_from, station_to), station_to))
        return edges

    
    def cal_dist(self, v1:Transit, v2:Transit) -> float:
        """
        return distance between v1 and v2 weighted by coefficient
        """
        x1,y1 = v1.x, v1.y
        x2,y2 = v2.x, v2.y
        coef = alpha
        if v1.type == 1 and v2.type == 1: coef = alpha2 # planet to planet
        elif v1.type == 2 and v2.type == 2: coef = 1 # station to station
        d = ((x1-x2)**2+(y1-y2)**2) * coef
        return d
    
    def cal_score(self):
        score = 0
        for i in range(len(self.order)-1):
            score += self.cal_dist(self.order[i], self.order[i+1])
        return int(pow(10,9)/(1000+score**0.5))

def trace(start:Transit, target:Transit, ancestors): 
    # s:source, t:target
    # dijksttra法の経路復元
    route = [target]
    now = target
    while True:
        pre = ancestors[now.key]
        route.append(pre)
        if pre == start:
            break
        now = pre
    route.reverse()
    return route

def dijkstra(start:Transit, target:Transit, links):
    heap = [(*l,start) for l in links[start.key]]
    heapq.heapify(heap)
    visited = set([start.key])
    ancestors = defaultdict(int)
    while heap:
        cost, to, ancestor = heapq.heappop(heap)
        if to.key in visited:
            continue
        visited.add(to.key)
        ancestors[to.key] = ancestor
        if to == target:
            return cost, trace(start,target,ancestors)
        for cost2, node2 in links[to.key]:
            if node2.key not in visited:
                heapq.heappush(heap, (cost+cost2, node2, to))
    return INF, None


class Output:
    
    def __init__(self, state:State) -> None:
        self.order = state.order
        self.stations = state.stations

    def ans(self):
        for transition in self.stations:
            print(transition.x, transition.y)
        print(len(self.order))
        for transition in self.order:
            print(transition.type, transition.id+1)

class Solver:
    def __init__(self, state:State) -> None:
        self.state = state

    def warshall_floyd(self):
        n = len(self.state.planets)
        dist = [[INF]*n for _ in range(n)]
        for i in range(n):
            dist[i][i] = 0
        for planet1 in self.state.planets:
            for planet2 in self.state.planets:
                dist[planet1.id][planet2.id] = self.state.cal_dist(planet1, planet2)
        for k in range(n):
            for i in range(n):
                for j in range(n):
                    dist[i][j] = min(dist[i][j], dist[i][k] + dist[k][j])
        return dist
    
    def solve(self):
        
        dist_matrix = self.warshall_floyd()

        self.state.order.append(self.state.planets[0])
        visited = [0]*len(self.state.planets)
        visited[0] = 1
        now = self.state.planets[0]
        next = Transit(-1,-1,-1,-1)
        n_visited = set([0])
        
        while len(n_visited) < len(self.state.planets):
            next_dist = []
            for i in range(len(self.state.planets)):
                next_dist.append((dist_matrix[now.id][i], i))
            next_dist = sorted(next_dist, key=lambda x:x[0])
            for i in range(len(self.state.planets)):
                if visited[next_dist[i][1]] == 1: continue
                next = self.state.planets[next_dist[i][1]]
                break
            _, route = dijkstra(now, next, self.state.links)
            for transition in route:
                self.state.order.append(transition)
            now = next
            visited[next.id] = 1
            n_visited.add(next.id)

        _, route = dijkstra(now, self.state.planets[0], self.state.links)
        for transition in route:
            self.state.order.append(transition)
    
        return self.state

def main():

    timeKeeper2 = TimeKeeper(0.8)

    parser = Parser(-1)
    input = parser.parse()
    
    planets = []
    for i in range(input.N):
        planets.append(Transit(id = i, x = input.ab[i][0], y = input.ab[i][1], type = 1))

    kmeans = Kmeans(planets, 100, 8)
    a = kmeans.clustering()
    stations = []
    for i in range(input.M):
        stations.append(Transit(id = i,x = a[i][0],y = a[i][1],type = 2))
    state = State([], planets, stations)
    solver = Solver(state)
    best_ans = solver.solve()
    best_score = best_ans.cal_score()
    eprint(timeKeeper2.time_msec(), best_score)

    tmp_stations = best_ans.stations
    
    while not timeKeeper2.isTimeOver():
        order = []
        stations = []
        for i in range(input.M):
            x_new = 0
            y_new = 0
            while True:
                x_new = tmp_stations[i].x+random.randrange(-20,20)
                y_new = tmp_stations[i].y+random.randrange(-20,20)
                if x_new >= 0 and x_new <= 1000 and y_new >= 0 and y_new <= 1000:
                    break
            stations.append(Transit(id = i,x = x_new, y = y_new, type = 2))
        state = State(order,planets,stations)
        solver = Solver(state)
        ans = solver.solve()
        score = ans.cal_score()
        if score > best_score:
            eprint(timeKeeper2.time_msec(), score)
            best_score = score
            best_ans = ans
            tmp_stations = stations
    eprint(best_score)
    output = Output(best_ans)
    output.ans()


if __name__ == "__main__":
    main()

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結果

テストケース

ソースコード